Senior Audio Research Engineer (m/f/d)
We are MYNT
Are you looking for a new challenge?
You've come to the right place if you're looking for a vibrant company to work for. At our office in Hamburg, you can expect to play a key as part of a highly passionate team that delivers stunning results.
Skills Required
• Demonstrable skills in Machine Learning applied to Audio Signals
• Demonstrable experience dealing with at least one type of Machine Learning algorithm (e.g., Deep Neural Networks, Hidden Markov Models, Support Vector Machines, Decision Trees etc.) applied to the processing of Audio Signals
• Good knowledge of Digital Signal Processing for Audio Signals
• Scripting and algorithm prototyping: Python, bash
• Development under Linux/Unix mandatory, Windows optional.
Desirable
• Experience with at least one standard Machine Learning package, amongst but not limited to: Tensorflow, Keras, MXNet, SciKit-Learn, Torch, Theano, HTK, Kaldi etc
• Signal processing with microphone arrays
• Advanced acoustics, e.g., sound field processing
• Programming: C/C++ coding and code optimisation
Personal Attributes
• Ability to deliver on research and evaluation methodology
• Good communication skills
• Excellent problem-solving skills
• Track record of academic publications or patent applications is required
• Enjoy working autonomously as a member of a team and mentoring teammates
• Self-confident and highly motivated
• Ability to deal confidently with a variety of people at all levels
• Able to manage own workload and meet deadlines
• Good organisational skills
• Good standard of written and spoken English
Education
Must have either a Master's degree or higher, or a PhD, with significant academic or industrial achievements in one of the following topics:
• Machine Learning applied to Audio Signals
• Digital Signal Processing of Audio Signals
• Automatic Speech/Speaker Recognition
• Music Information Retrieval
• Acoustic Events Detection
• Statistical Speech Synthesis
• Thematic Indexing of Audio tracks (e.g., Speaker Diarization, Acoustic Segmentation of Video Documents etc.)
Experience
• Five years' industrial experience if you hold a Master's degree; or
• PhD with four years post-doctoral or industry experience in a related area or;
• An equivalent combination of education and experience in an appropriate field.
• Demonstrable skills in Machine Learning applied to Audio Signals
• Demonstrable experience dealing with at least one type of Machine Learning algorithm (e.g., Deep Neural Networks, Hidden Markov Models, Support Vector Machines, Decision Trees etc.) applied to the processing of Audio Signals
• Good knowledge of Digital Signal Processing for Audio Signals
• Scripting and algorithm prototyping: Python, bash
• Development under Linux/Unix mandatory, Windows optional.
Desirable
• Experience with at least one standard Machine Learning package, amongst but not limited to: Tensorflow, Keras, MXNet, SciKit-Learn, Torch, Theano, HTK, Kaldi etc
• Signal processing with microphone arrays
• Advanced acoustics, e.g., sound field processing
• Programming: C/C++ coding and code optimisation
Personal Attributes
• Ability to deliver on research and evaluation methodology
• Good communication skills
• Excellent problem-solving skills
• Track record of academic publications or patent applications is required
• Enjoy working autonomously as a member of a team and mentoring teammates
• Self-confident and highly motivated
• Ability to deal confidently with a variety of people at all levels
• Able to manage own workload and meet deadlines
• Good organisational skills
• Good standard of written and spoken English
Education
Must have either a Master's degree or higher, or a PhD, with significant academic or industrial achievements in one of the following topics:
• Machine Learning applied to Audio Signals
• Digital Signal Processing of Audio Signals
• Automatic Speech/Speaker Recognition
• Music Information Retrieval
• Acoustic Events Detection
• Statistical Speech Synthesis
• Thematic Indexing of Audio tracks (e.g., Speaker Diarization, Acoustic Segmentation of Video Documents etc.)
Experience
• Five years' industrial experience if you hold a Master's degree; or
• PhD with four years post-doctoral or industry experience in a related area or;
• An equivalent combination of education and experience in an appropriate field.
Interested? Apply now: